Computer Systems:
In most companies, computers have historically been controlled by accounting departments where the accounting oriented mangers have developed computer systems which, like their accounting systems, are deterministic, viewing the present and future in the same manner as the past. But the present is a moving point in time, cannot be "frozen," and must be constantly updated. The past can be viewed as a fact, more or less "hard," depending on the quality and quantity of records made at or near the time of occurrence and on the interim system of fact preservation. But, the future should be viewed not as fact but as multiple alternate sequences of probably events. Sometimes the future can be reasonably predicted by an extrapolation of the past, but probabilistic uncertainty should always be considered, because uncertainty is real.
Scheduling Systems:
Most scheduling systems were developed to serve accounting oriented managers who wanted to treat the future as factually as the past. One example of this is the notion that future events can be scheduled, in detail, in advance. The truth is that both known and unknown variables introduce uncertainty which defy precise detailed scheduling. These variables frequently produce bottlenecks and resource shortages that require real-time schedule revisions. In most organizations the ability to report or willingness to admit that schedule revisions are necessary is always awkward and is sometimes subject to punishment. As a result, the real world in the organization is quite different from the computer system's view.
Manufacturing Systems:
In regard to manufacturing scheduling, rescheduling and delivery, a manufacturing organization is continually receiving orders for products that require the shared use of resources and workspaces with conflicting time requirements. Without reliable knowledge of the existence of resources and time constraints of resources ("availability") an organization is unable to accurately forecast its ability to meet requested deliveries.
Current scheduling practices almost never compare, or even consider, commitments made versus actual resources available over a finite period of time. Traditionally, allocations are made against historical capacity and result in an arbitrary production target either in dollars or a mixture of product units. Under currently used scheduling systems, attempts to measure capacity limitations due to resource constraints typically utilize an iterative process that requires so much computer capacity that it is never current, except in a very general and only approximate sense. This is reflective of the recognition that iterative processes are useful only for systems that converge to an asymptotic valve, e.g., a constant supply figure, such as 10 gallons paint per day.
In contrast, where set points vary frequently, while current systems attempt to allocate resources, they almost never consider real time changes in actual schedules. Production is presumed to proceed according to schedule. As a result, most production schedules include operations that were "supposed to have been completed" but were not, and the subsequent departments are not informed, resulting in complete disruption of forward scheduling. Such current systems, which view the future deterministically (deterministic modeling), result in underutilized major resources (like machine tools), and heavy duplication of floating resources (like tools, fixtures, and inventory) and still do not achieve time production.
The conventional Manufacturing Requirements Planning Systems (MRP Systems) have two traps which must be avoided:
1. The first trap is related to the processing of the data by computer systems. The sheer quantity of data involved in planning the utilization of every resource in the production of a product cause even large computers to grind to a halt when traditional forward-chaining programming approaches are used. It is a "long way" from the product back through all its sub-assemblies, components, and resources to the workspace and most systems cannot follow that long a path in a reasonable amount of time, let alone consider any of the alternate probable paths at each branch. PA1 2. The second trap is related to the competitive strength of the organization: When a product is defined in enough detail for the Conventional MRP System to plan all resources back to the Workspaces used to produce that product, the tendency will be to "freeze" the processes for producing that product. No further improvements will be made in production, safety, hassle factor, consistency, or costs. Benefits of new production techniques will be lost. The organization is a standing target for its competitors who might learn to employ better production methods. An effective decision support system will assist an organization in examining alternative production methods, learning better paths, and recommending global improvements.
In the broader view, these two traps are those of micro-scheduling, looking at data apart from the meaning of that data for scheduling, as a result of which product design change becomes inflexible, a victim of the scheduling demand.
New Product Design:
In regard to management of new product design, an organization must have or develop manufacturing capabilities or sources of supply for the component parts of its proposed new products. More specifically, the limits of existing production capacity cannot be exceeded without either: (1) adding resources (labor, machines, fixtures, tooling, etc.); or (2) finding new outside resources; or (3) process improvements (yield and throughput).
Product design engineers almost never consider the limits of established internal or external capabilities when designing new products. For example, a design engineer may typically design a new product with, say, a 0.25 inch diameter hole 12 inches deep without ever first determining whether or not: (1) a drill that size and that long exists in the tool inventory (or even in a drill vendor's catalog); or (2) a machine exists in-house (or even at an establishment subcontractor's plant) capable of drilling a 12 inch deep hole. Manufacturing capability is not a typical concern for a design engineer. Rather, it is taken erroneously as a given.
As a result, it is not uncommon for shop floor workers to be the discoverers of the fact that tools, fixtures and even machines do not exist to, say, drill a 0.025 inch diameter hole 12 inches deep. All too often this discovery is made just before a new product is supposed to be shipped to a customer. The iterative recovery process that results is usually embarrassing, expensive, people intensive, and time consuming; but it has become so common that it is wryly expected as normal.
Unfilled Need in the Art:
The above are just a few areas in which current scheduling systems are wholly inadequate to deal with the ever increasing complexity of efficiently manufacturing high technology, multi-component products, and more generally to manage effective resource utilization. Accordingly, there is an enormous, unmet need for realistic scheduling and effective resource utilization.